A comprehensive evaluation of natural selection and genetic constraints as predictors of evolutionary divergence

A major unresolved question in evolutionary biology is whether macroevolution (the evolutionary divergence of populations and species) can be understood by considering microevolutionary processes (selection, evolvability) operating within populations.

Although patterns of standing genetic variation suggests substantial evolutionary potential of most phenotypic traits, recent studies suggest that limited genetic variation for specific traits or trait combinations can constrain evolutionary divergence.

Furthermore, the relative roles of such constraints vs. spatiotemporal variation in natural selection in driving evolutionary divergence are poorly understood.

Answering these questions requires comprehensive datasets including replicated estimates of phenotypic selection and trait evolvability, as well as data on the divergence of populations obtained in a common environment.

While each of these data types are available for many systems, all necessary data are rarely available for the same system, precluding integrated analyses.

This project will complete one such dataset through field and greenhouse studies of a plant model system and combine it with databases of selection, evolvability and population divergence compiled from the literature.

By studying the evolution of complex phenotypes in our model system and through meta-analyses across diverse systems, we aim to provide empirical, technical, and conceptual advances in the study of multivariate phenotypic evolution.